MHC Class II Restricted Innate-Like Double Negative T Cells Contribute to Optimal Primary and Secondary Immunity to Leishmania major
Bibliographic record
Abstract
Although it is generally believed that CD4(+) T cells play important roles in anti-Leishmania immunity, some studies suggest that they may be dispensable, and that MHC II-restricted CD3(+)CD4(-)CD8(-) (double negative, DN) T cells may be more important in regulating primary anti-Leishmania immunity. In addition, while there are reports of increased numbers of DN T cells in Leishmania-infected patients, dogs and mice, concrete evidence implicating these cells in secondary anti-Leishmania immunity has not yet been documented. Here, we report that DN T cells extensively proliferate and produce effector cytokines (IFN-γ, TNF and IL-17) and granzyme B (GrzB) in the draining lymph nodes and spleens of mice following primary and secondary L. major infections. DN T cells from healed mice display functional characteristics of protective anti-Leishmania memory-like cells: rapid and extensive proliferation and effector cytokines production following L. major challenge in vitro and in vivo. DN T cells express predominantly (> 95%) alpha-beta T cell receptor (αβ TCR), are Leishmania-specific, restricted mostly by MHC class II molecules and display transcriptional profile of innate-like genes. Using in vivo depletion and adoptive transfer studies, we show that DN T cells contribute to optimal primary and secondary anti-Leishmania immunity in mice. These results directly identify DN T cells as important players in effective and protective primary and secondary anti-L. major immunity in experimental cutaneous leishmaniasis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".